Non Sorting Genetic Algorithm II (NSGA-II)

Bearable and compressed implementation of Non Sorting Genetic Algorithm II (NSGA-II)
Updated 25 Nov 2019

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This function performs a Non Sorting Genetic Algorithm II (NSGA-II) for minimizing continuous functions. The implementation is bearable, computationally cheap, and compressed (the algorithm only requires one file: NSGAIII.m). An 'example.m' script is provided in order to help users to use the implementation. It is also noteworthy to mention that the code is highly commented for easing the understanding. This implementation is based on the paper of Deb et al. (2002), "A fast and elitist multiobjective genetic algorithm: NSGA-II".

Cite As

Víctor Martínez-Cagigal (2024). Non Sorting Genetic Algorithm II (NSGA-II) (, MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2017a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes

The old mutation operator is substituted by a weighted normal distribution approach, as suggested by Alexander Hagg, which reaches faster convergences.

True ParetoFronts for the examples are now uploaded